Efficiency evaluation of the photocatalytic degradation of zinc oxide nanoparticles immobilized on modified zeolites in the removal of styrene vapor from air

Styrene monomer is a volatile organic compound that has many applications in plastics, rubber, and paint manufacturing industries. Exposure to styrene vapor has certain effects, including suppression of the central nervous system, loss of concentration, weakness and fatigue, and nausea and there is a possibility of carcinogenesis in long-term exposure. Therefore, it is necessary to control and eliminate this vapor. The aim of this study was to investigate the performance of zinc oxide nanoparticles on modified natural zeolites in removing styrene vapor from the air. Natural zeolites of clinoptilolite were modified using hydrochloric acid and diphenyldichlorosilane. Next, zinc oxide nanoparticles with different ratios of 3, 5, and 10 wt% were stabilized on the zeolites. To determine their characteristics, samples were used from BET, SEM and XRD analyses. The input styrene concentration and the ratio of nanoparticles stabilized on zeolites were studied as effective functional parameters on the removal process. The efficiency results of natural zeolites (Ze) and modified zeolites (Mze) in styrene adsorption from the air show that the styrene breakthrough in the bed of MZe compared to that of Ze increases approximately two times. Also, the results showed that the removal by the process of UV/MZe-ZnO 3%, UV/MZe-ZnO 5%, and UV/MZe-ZnO 10%, was 36.5%, 40%, and 26%, respectively. From the results it can be concluded that MZe can increase the efficiency of photocatalytic degradation. Clinoptilolites of Iran can be used as an adsorbent to remove polluted air in industries that have low concentrations and flow rates.     

Effect of modified single‐wall carbon nanotubes on mechanical and morphological properties of thermoplastic elastomer nanocomposites based on (polyamide 6)/(acrylonitrile butadiene rubber)

Thermoplastic elastomer nanocomposites based on acrylonitrile butadiene rubber (NBR) and polyamide 6 (PA6), with acid functionalized single‐wall carbon nanotubes (SWNT), were prepared via a direct melt‐mixing process in an internal mixer. The influence of SWNT content (0, 0.5, 1, 1.5) on morphological properties of PA6/NBR with different ratios (80/20, 70/30, 60/40) were then investigated. Characterization of nanocomposites was conducted by using transmission electron microscopy, scanning electron microscopy, differential scanning calorimetry, and mechanical properties. Scanning electron microscopy micrographs proved the droplet‐matrix blend morphology in which the size of NBR droplets decreased as the SWNT loading increased, suggesting dispersion of SWNT in the PA6 phase. It was further proved by transmission electron microscopy images, showing homogenous dispersion of SWNT in the PA6 phase. Differential scanning calorimetry results showed a slightly reduced percentage of crystallinity in samples containing SWNT. The mechanical properties of nanocomposites indicated an enhancement in tensile strength, modulus, and hardness on increasing SWNT content. J. VINYL ADDIT. TECHNOL., 22:336–341, 2016. © 2014 Society of Plastics Engineers     

Numerical investigation of grooves effects on the thermal performance of helically grooved shell and coil tube heat exchanger

Heat exchangers are integral parts of important industrial units such as petrochemicals, medicine and power plants. Due to the importance of systems energy consumption, different modifications have been applied on heat exchangers in terms of size and structure. In this study, a novel heat exchanger with helically grooved annulus shell and helically coiled tube was investigated by numerical simulation. Helically grooves with the same pitch of the helical coil tube and different depth are created on the inner and outer wall of annulus shell to improve the thermal performance of heat exchanger. In the first section, thermal performance of the shell and coil heat exchanger with the helical grooves on its outer shell wall was compared with same but without helical grooves. At the second section, helically grooves created on both outer and inner wall of the annulus shell with different groove depths. The results showed that the heat exchanger with grooves on both inner and outer shell wall has better thermal performance up to 20% compared to the heat exchanger with grooves on only outer shell wall. The highest thermal performance achieves at lower flow rates and higher groove depths whereas the pressure drop did not increase significantly.     

Fault diagnosis of an automobile cylinder head using low frequency vibrational data

This paper proposes a vibration-based fault-diagnosis method for mechanical parts. This method, after algorithm development, only requires a single inexpensive test to inspect the part which could take as short as half a second. The algorithm is developed in three major stages, (i) exciting specimens without or with known faults using a controlled force and recording acceleration of a single point for a short time (ii) finding a signature for each faulty specimen, using Fourier transform and statistical analysis. (iii) Developing a multi-layer perceptron, as a mathematical model, using the results of stage (ii). The elements of a part signature are the inputs to the model. The location (and possibly size and shape factor) of the fault is model output. Stage (i) can be performed experimentally or alternatively with a validated FEM, one experiment or simulation per specimen. The proposed technique was examined to locate (isolate) a fault on an automobile cylinder head. The presented accuracy is considerable, and the data collected at fairly low frequency range (below 1200 Hz) were found to be sufficient for this technique. In the case study of this paper, possible fault locations are on a line; as a result, fault location has one dimension. It is shown that the technique can be extended to higher dimensions.     

Mechanochemical sulfidization of a mixed oxide-sulphide copper ore by co-grinding with sulfur and its effect on the flotation efficiency

Mechanochemical sulfidization of a mixed sulfide/oxide copper ore by co-grinding with sulfur and additives including Mg(NO₃)₂ and Fe(NO₃)₃ salts and iron, aluminum and magnesium powders was investigated for the first time. Also, the influence of sulfidization during the wet-milling process was examined on the separation efficiency and recovery of copper in detail. The results demonstrated that co-grinding with sulfur solely had the best flotation performance at the value of 0.5 wt.% and it was attributed to the possible existence of S-O bonding on copper oxides surfaces. In addition, adding magnesium nitrate salt, magnesium powder, iron nitrate salt and aluminum powder as additive associated with 0.5 wt% sulfur into ball milling caused the flotation improvement at the amounts of 0.2 wt%, 0.2 wt%, 0.5 wt% and 0.5 wt%, respectively. Also, the effect of grinding time and sulfidization pH with 0.5 wt% sulfur solely was determined and pHs of 7.5 to 8.5 gave the best results. The highest recovery (75.76%) and separation efficiency (63.44%) were achieved at pH of 7.5 and 8.5, respectively.     

Flexural and Charpy impact behaviour of epoxy/glass fabric treated by nano-SiO2 and silane blend

A sizing formulation, containing compatible and incompatible silane coupling agents with epoxy resin in conjunction with nanoscale colloidal silica, was used to modify the surface of glass fabric. The modified glass fabric/epoxy resin composite panels were fabricated and characterised by flexural test, Charpy impact test and scanning electron microscope (SEM). By combining nano silica with silane blend in the fabric sizing, more energy was consumed under bending and impacting, which resulted in an improvement of the toughness in composites. The flexural strength, bending stain and Charpy impact strength of the epoxy composite/glass fabric treated with 1?wt-% nano silica and silane blend were ～42, ～22 and 35%, respectively, higher than those of silane blend coated glass fabric-reinforced composites (without nano silica). Furthermore, the change of the brittle fracture of the composite into ductile fracture was investigated by SEM micrographs. A possible toughening mechanism was also proposed.     

Modelling qualitative and quantitative parameters of groundwater using a new wavelet conjunction heuristic method: wavelet extreme learning machine versus wavelet neural networks

In recent years, as a result of climate change as well as rainfall reduction in arid and semi‐arid regions, modelling qualitative and quantitative parameters belonging to aquifers has become crucially important. In Iran, as aquifers are treated as the most commonly used drinking water resources, modelling their qualitative and quantitative parameters is enormously important. In this paper, for the first time, values of salinity, total dissolved solids (TDS), groundwater level (GWL) and electrical conductivity (EC) of the Arak Plain, located in Markazi Province, Iran, are simulated by means of four modern artificial intelligence models including extreme learning machine (ELM), wavelet extreme learning machine (WELM), online sequential extreme learning machine (OSELM) and wavelet online sequential extreme learning machine (WOSELM) as well as the MODFLOW software for a 15‐year period monthly. To develop the hybrid artificial intelligence models, the wavelet is employed. First, the effective lags in estimating the qualitative and quantitative parameters of the groundwater are identified using the autocorrelation function (ACF) and the partial autocorrelation function (PACF) analysis. After that, four different models are developed by the selected input combinations and also the ACF and the PACF in the form of different lags for each of ELM, WAELM, OSELM and WOSELM methods. Then, the superior models in simulating the groundwater qualitative and qualitative parameters are detected by conducting a sensitivity analysis. To forecast the electrical conductivity (EC) by the best WOSELM model, the values of the Nash–Sutcliffe efficiency coefficient (NSC), Mean Absolute Error (MAE) and the scatter index (SI) are obtained to be 0.991, 18.005 and 4.28E‐03, respectively. In addition, the most effective lags in estimating these parameters are introduced. Subsequently, the results found by the MODFLOW model are compared with those of the artificial intelligence models and it is concluded that the latter are more accurate. For instance, the scatter index and Nash–Sutcliffe efficiency coefficient values calculated by WOSELM for TDS, respectively, are 5.34E‐03 and 0.991. Finally, an uncertainty analysis is conducted to evaluate the performance of different numerical models. For example, MODFLOW has an underestimated performance in simulating the salinity parameter.     

Effect of process variables on product yield distribution in thermal catalytic cracking of naphtha to light olefins over Fe/HZSM-5

The effect of temperature, WHSV and Fe loading over HZSM-5 catalyst in thermal-catalytic cracking (TCC) of naphtha for the production of light olefins has been studied. The response surface defined by three most significant parameters is obtained from Box-Behnken design method and the optimal parameter set is found. The results show that ethylene increases with temperature, while propylene shows an optimum at 650 °C. Moderate WHSV is favorable for maximum production of light olefins. Addition of Fe to HZSM-5 has a favorable effect on the production of light olefins up to 6% of loading. Excess amount of loading decreases the conversion of naphtha, which leads to a drop in light olefin yields. The yield of light olefins (ethylene and propylene) at 670 °C, 44 hr⁻¹ and 6 wt% Fe has been increased to 5.43 wt% compared to the unmodified HZSM-5 and reaches to 42.47 wt%.